DETAILED ACTION
This is in response to Request for Continued Examination (RCE) filed on 03/17/2026. Claims 1-20 are pending in this Office Action.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 03/17/2026 has been entered.
Remark
In response filed 03/17/2026, claims 1, 12, and 20 have been amended, no claim has been cancelled, and no new claim has been added.
The Applicant’s amendments regarding 35 USC 101 rejection of claim 20 for being directed to non-statutory subject matter of signal per se accepted by the Examiner. Therefore, prior 35 USC 101 rejection of claim 20 is withdrawn.
Response to Arguments
Applicant's arguments filed 03/17/2026 have been fully considered but they are not persuasive.
The applicant argues:
Applicant submits that the claims cannot be considered abstract as directed to a mental process. For instance, in claim 1, at least "performing, with a tree neural network (TNN), prediction according to the historical access data and the child node to determine a predicted future situation based on a potential impact of the at least one alternative strategy of the child node", "generating, based on the prediction performed according to the historical access data and the child node, at least one extension node in the tree-structured data, the at least one extension node comprising an alternative strategy generated based on the predicted future situation determined based on the potential impact of the at least one alternative strategy of the child node", "encoding the tree-structured data comprising the root node, the at least one child node, and the at least one extension Application Serial No. 18
node with a graph neural network (GNN) to generate a first state vector that integrates the predicted future situation", and "executing, by a storage controller, the retention strategy in a data retention environment" cannot be considered a mental process because the steps are not practically performed in the human mind. For example, the human mind is not equipped to perform at least this claim limitation because the human mind is not equipped to perform a several-step manipulation of data. See e.g., Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1147-49, 120 USPQ2d 1473, 1480-81 (Fed. Cir. 2016).
The Examiner respectfully disagrees.
It is essential that the broadest reasonable interpretation (BRI) of the claim be established prior to examining a claim for eligibility. The BRI sets the boundaries of the coverage sought by the claim and will influence whether the claim seeks to cover subject matter that is beyond the four statutory categories or encompasses subject matter that falls within the exceptions. Evaluating eligibility based on the BRI also ensures that patent eligibility under 35 USC 101 does not depend simply on the draftsman’s art. See MPEP 2106.II.
In Prong One of Step 2A, it is asked whether the claim recite a judicial exception such as an abstract idea. The abstract ideas include the enumerated groupings defined as:
1) Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations (see MPEP § 2106.04(a)(2), subsection I);
2) Certain methods of organizing human activity –and
3) Mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion) (see MPEP § 2106.04(a)(2), subsection III).
The Examiner holds that claim 1 is directed to judicial exception for reciting mental process and mathematical concept. As set forth in the Step 2A, Prong 1 analysis, the above-mentioned steps of “performing…prediction according", "generating, based on the prediction performed according to the historical access data and the child node, at least one extension node…", and "encoding the tree-structured data comprising the root node…" are recited at a high level of generality and based on broadest and reasonable interpretation (BRI), it involves the concepts of observation, evaluation and/or judgement which could be practically performed in the human mind. See below for details.
With respect to the steps "executing, by a storage controller, the retention strategy in a data retention environment", the Examiner agrees that it is not a mental process. However, it is an additional limitation that under Step 2A, Prong 2 and Step 2B are considered to be extra-solution and/or well-understood, conventional, and routine activity. See below for details.
As such, the above-mentioned steps are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Therefore, claim 1 recite a judicial exception. Therefore, claims 1, 12, and 20 analyzed under Step 2A, Prong 1 are directed to judicial exception of abstract idea.
The applicant further argues:
Applicant submits that the claims integrate any alleged abstract idea into a practic assuming arguendo, the claims do recite a judicial exception (e.g., a mental process) that can be practically performed in the human mind, Applicant submits that the claims integrate any alleged abstract idea into a practical application that improves the functioning of a computer
… Through this method, predicted future states can be integrated in a process of generating the retention strategy, which provides a more comprehensive perspective for decision-making, thereby improving the accuracy and effectiveness of the retention
strategy, and improving the utilization of storage resources.
Additionally, the state vector integrates predictions of future states, thereby providing a more comprehensive and in-depth perspective for a decision-making process and the technique of formulating a forward-looking strategy not only enhances the accuracy and effectiveness of a retention strategy, but also significantly improves the utilization efficiency of storage resources.
The Examiner respectfully disagrees.
As it is established in Step 2A, Prong 1, claim 1 is directed to judicial exception of abstract idea. A judicial exception (e.g., abstract idea) by itself cannot improve a computer function or technology. Claim 1 further recites some additional limitations. However, these additional limitations are recited at a high level of generality without providing enough technical details on how to achieve the result. Therefore, under BRI these additional limitations are no more than extra-solution activities or merely linking the judicial exception to the technological environment of a computer.
For instance, the additional step of “executing, by a storage controller, the retention strategy in a data retention environment” and the generic computer components of “a storage controller“, “an electronic device”, “a processor", “a memory”, "a computer-readable medium" and/or “a machine” are recited so generically that they represent no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(I) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224-26 (2014). Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Moreover, the additional elements of using “a tree neural network (TNN)”, “a graph neural network (GNN)”, and “a reinforcement learning model” recited at a high level of generality and merely invokes a machine learning algorithm to perform, encode, or select without providing any technological details as to how said operations are performed. Using the machine learning algorithm (e.g., TNN, GNN, or a learning model) to merely perform an operation without providing any technical details is extra-solution activity to the central idea of claims. Such insignificant extra-solution activity does not lend patent eligibility to the abstract idea of the claims by integrating the abstract idea into a practical application.
Additionally, the amended limitation of “performing, with a tree neural network (TNN), prediction according to the historical access data and the child node to determine a predicted future situation based on a potential impact of the at least one alternative strategy of the child node” is recited at a high level of generality lacking sufficient “technical details” on how to achieve the results. At that level of generality, the claims do no more than describe desired function or outcome, without providing limiting details that confine the claimed to a practical solution to an identified problem. The features of using a learning model (e.g., a TNN or GNN) to output a prediction based on input data is without providing limiting details that confine the claimed to a practical solution to an identified problem is an extra-solution activity the central idea of claims. An invocation to use such an old technology in the manner it is intended to be used for its ordinary purpose is both generic and well-understood and conventional activity. They do not describe any particular improvement in the manner of computer functions.
The courts have identified that “adding insignificant extra-solution activity to the judicial exception” did not integrate a judicial exception into a practical application. See MPEP 2106.04(d) and 2106.05(g).
Therefore, these additional elements do not: (1) improve the functioning of a computer or other technology; (2) are not applied with any particular machine (except for a generic computer); (3) do not effect a transformation of a particular article to a different state; and (4) are not applied in any meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. See MPEP §§ 2106.05(a)-(c), (e)-(h). In other words, the aforementioned additional element (or combination of elements) recited in the claims do not integrate the judicial exception into a practical application.
In conclusion, since the steps of the claims along with the additional limitations are recited at that level of generality, the claims do no more than describe desired function or outcome, without providing limiting technical details that confine the claimed to a practical solution to an identified problem. They do not describe any particular improvement in the manner of computer functions. The recited additional limitations are insignificant extra-solution activities that do not lend patent eligibility to the abstract idea of the claims by integrating the abstract idea into a practical application. Therefore, claim is incapable of improving a manner in which a computer functions or other technology.
Therefore, based on above explanation and reasoning the 35 USC 101 rejection of claims 1-20 for being directed to judicial exception of abstract idea are maintained.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter of abstract ideas.
Step 1:
Claims 1-20 are directed to a method/device/storage medium which is one of the statutory categories of invention.
Step 2A:
Prong 1:
Claims 1, 12, and 20 are directed to an abstract idea without significantly more.
The claims recite the steps of:
determining, based on a current data parameter, a root node in tree-structured data and representing a
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current state; [recited at a high level of generality and based on broadest and reasonable interpretation (BRI), it involves the concepts of observation, evaluation and/or judgement which could be practically performed in the human mind.]
determining, based on historical access data, at least one child node of the root node, the child node comprising at least one alternative strategy; [recited at a high level of generality and based on BRI, it involves the concepts of observation, evaluation and/or judgement which could be practically performed in the human mind.]
performing…prediction according to the historical access data and the child node to determine a predicted future situation based on a potential impact of the at least one alternative strategy of the child node; [recited at a high level of generality and based on BRI, it involves the concepts of observation, evaluation and/or judgement which could be practically performed in the human mind. A person can mentally make a prediction of future situation and potential impact of a situation based on the past data]
generating, based on the prediction performed according to the historical access data and the child node, at least one extension node in the tree-structured data, the at least one extension node comprising an alternative strategy generated based on the predicted future situation determined based on the potential impact of the at least one alternative strategy of the child node; [recited at a high level of generality and based on BRI, it involves the concepts of observation, evaluation and/or judgement which could be practically performed in the human mind. A human being (e.g., a developer) can manually and mentally generate nodes based on prediction data that include user-defined data]
encoding the tree-structured data comprising the root node, the at least
one child node, and the at least one extension node…to generate a first state vector that integrates the predicted future situation; [recited at a high level of generality and based on BRI, encoding a tree-structured data to a vector involves mathematical calculations. It also involves concepts of evaluation and judgement that could be practically be performed in the human mind. A human being (e.g., a developer) can manually and mentally convert a tree structured data to numerical representations (a vector) using mathematical calculations. It does not require a computer to convert a data structure into its numerical representations] and
selecting…the alternative strategy corresponding to the at least one child node or the at least one extension node based on the first state vector to generate the retention strategy. [recited at a high level of generality and based on BRI, it constitutes concepts of observation, evaluation and/or judgement which could be practically performed in the human mind. A human being (e.g., a developer) can manually and mentally select an alternative strategy based on numerical representations of data]
As such, the above-mentioned steps are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is, nothing in the claim element precludes the step from practically being performed in a human mind or with pen and paper. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas (concepts performed in the human mind including an observation, evaluation, judgment, and opinion).
Prong 2:
This judicial exception recited in claims 1, 12, and 20 is not integrated into a practical application. The claimed additional step of “executing, by a storage controller, the retention strategy in a data retention environment” recited at a high level of generality and based on BRI, it represents no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer.
Moreover, the claimed additional elements of using “a tree neural network (TNN)”, “a graph neural network (GNN)”, and “a reinforcement learning model” recited at a high level of generality and merely invokes a machine learning algorithm to perform, encode, or select without providing any technological details as to how said operations are performed. Using the machine learning algorithm (e.g., TNN, GNN, or a learning model) to merely perform an operation without providing any technical details is extra-solution activity to the central idea of claims. Such insignificant extra-solution activity does not lend patent eligibility to the abstract idea of the claims by integrating the abstract idea into a practical application.
Furthermore, the claims recite generic computer components of “a storage controller“, “an electronic device”, “a processor", “a memory”, "a computer-readable medium" and/or “a machine.” Said generic computer components are recited so generically that they represent no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(I) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224-26 (2014). Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
These additional elements do not: (1) improve the functioning of a computer or other technology; (2) are not applied with any particular machine (except for a generic computer); (3) do not effect a transformation of a particular article to a different state; and (4) are not applied in any meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. See MPEP §§ 2106.05(a)-(c), (e)-(h). In other words, the aforementioned additional element (or combination of elements) recited in the claims do not integrate the judicial exception into a practical application.
Step 2B:
Claims 1, 12, and 20 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claimed additional step of “executing, by a storage controller, the retention strategy in a data retention environment” recited at a high level of generality and based on BRI, it represents no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer.
Moreover, the claimed additional elements of using “a tree neural network (TNN)”, “a graph neural network (GNN)”, and “a reinforcement learning model” recited at a high level of generality and merely invokes a machine learning algorithm to perform, encode, or select without providing any technological details as to how said operations are performed. Using the machine learning algorithm (e.g., TNN, GNN, or a learning model) to merely perform an operation without providing any technical details is a well-understood, conventional, and routine activity. The feature of using a machine learning function to process data is a conventional and well-understood function in the art (See for example Koudas et al., US 2009/0319518, paragraph 130) which is simply appending well-understood, routine, conventional activities previously known to the industry, specified at high level of generality to the general exception (See MPEP 2106.05(d)). Thus, the claimed additional elements individually and in combination do not amount significantly more than abstract idea.
Furthermore, the claims recite generic computer components of “a storage controller“, “an electronic device”, “a processor", “a memory”, "a computer-readable medium" and/or “a machine.” Said generic computer components are recited so generically that they represent no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(I) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224-26 (2014). Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Therefore, claims 1, 12, and 20 are not patent eligible.
Regarding dependent claims 2-4, 6, 8, 13-15, 17, and 19,
the dependent claims further recite the additional steps for encoding nodes, encoding edges, determining, generating simulation, calculating value, and/or generating retention strategy that could be performed mentally failing to integrate the judicial exception into a practical application or to amount significantly to more than abstract idea.
Furthermore, the step of updating the child node in the dependent claim 3 recited at a high level of generality is considered to be an insignificant extra solution and/or a well-understood routine computer routine of updating data failing to integrate the judicial exception into a practical application or to amount significantly to more than abstract idea.
Regarding dependent claims 5, 7, 9, 10, 16, and 18,
the dependent claims further recite the additional step for determining, generating nodes, generating training nodes, and/or generating vector that could be performed mentally failing to integrate the judicial exception into a practical application or to amount significantly to more than abstract idea.
Moreover, the dependent claims recite additional limitation of using “a prediction model”, selecting alternative strategy using “a reinforcement learning model”, and “training the reinforcement learning model” at a high level of generality that are no more than insignificant extra solution and/or well-understood routine computer routines failing to integrate the judicial exception into a practical application or to amount significantly to more than abstract idea. Said elements are recited at a high level of generality and merely invokes “a machine learning algorithm” to select a retention strategy without providing any technological details as to how such a retention strategy is selected. The step of training the machine learning algorithm is also an extra-solution activity to the central idea of claims.
At that level of generality, the claims do no more than describe desired function or outcome, without providing limiting details that confine the claimed to a practical solution to an identified problem. The recited features of training and using models are extra-solution activities the central idea of claims. An invocation to use such an old technology in the manner it is intended to be used for its ordinary purpose is both generic and well-understood and conventional activity. They do not describe any particular improvement in the manner of computer functions. Such insignificant extra-solution activity does not lend patent eligibility to the abstract idea of the claims by integrating the abstract idea into a practical application. See MPEP 2106.04(d) and 2106.05(g).
Moreover, the feature of using a machine learning function to process data is a conventional and well-understood function in the art (See for example Koudas et al., US 2009/0319518, paragraph 130) which is simply appending well-understood, routine, conventional activities previously known to the industry, specified at high level of generality to the general exception (See MPEP 2106.05(d)). Thus, the claimed additional elements individually and in combination do not amount significantly more than abstract idea. Furthermore, the step of training the model is also considered to be a well-known and well-understood computing activity previously known to the industry that specified at high level of generality to the general exception (for example see prior art Huang et al, US 20160294759 [paragraph 50, last three lines] and Kirshenbaum, US
2003/0191726 [paragraph 120]).
Additionally, the step of “executing the third retention strategy…” is considered to be as “apply it” which do not integrate the recited abstract idea into a practical
application or add to more than abstract idea.
Therefore, the dependent claims lack additional elements that sufficient to
integrate the judicial exception into a practical application or amount to significantly more than abstract idea found in the independent claims.
Regarding claim 11,
the claim includes non-functional description material defining data in a node which is not sufficient to integrate the judicial exception into a practical application or amount to significantly more than abstract idea found in the independent claim.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Wang et al., US 2025/0370956 disclosing a method includes determining, based
on historical access data and a current data parameter, a root node representing a current state and at least one child node including an alternative strategy, generating at least one extension node including an alternative strategy based on predictions of the historical access data and the at least one child node, generating a first state vector by encoding tree-structured data including the root node, the child node, and the extension node, selecting the alternative strategy corresponding to the child node or the extension node based on the first state vector to generate the retention strategy.
Yarlagadda et al., US 2023/0079486 disclosing a first archive of a first snapshot of a source storage is caused to be stored to a remote storage. At least a portion of content of the first archive is stored in data chunks stored in a first chunk object of the remote storage and the first archive is associated with a first data policy. A second archive of a second snapshot of the source storage is caused to be stored to the remote storage. At least a portion of content of the second archive is referenced from data chunks stored in the first chunk object and the second archive is associated with a second data policy. Policy compliance of the chunk object storing data chunks referenced by the first archive and the second archive that are different is automatically managed based on the first data policy and the second data policy that are different.
Points of Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HARES JAMI whose telephone number is (571)270-1291. The examiner can normally be reached M-F 9:00a-5:00p.
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/Hares Jami/ Primary Examiner, Art Unit 2164
06/10/2026
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